This is a fast-growing AI company focused on expanding human potential through applied AI research and product innovation. Its mission is to build enterprise-grade AI systems that do more than answer questions: they help organisations execute work, connect tools, and automate complex business processes end to end.
The company is developing a next-generation platform designed to act as the “brain of the enterprise”, integrating multiple SaaS tools and using AI agents to carry out workflows intelligently, safely, and at scale. The culture is highly technical, research-driven, and strongly oriented towards real-world deployment. It values frontier thinking, practical impact, rapid learning, and collaboration between research and product teams.
As a Research Engineer, you will lead applied research in LLMs, agents, and machine learning with a clear production focus. Your work will help solve the hardest technical problems in long-horizon agent performance, including reasoning quality, retrieval and planning, memory, tool use, and multi-agent coordination.
You will design, compare, and improve agent harnesses; build rigorous benchmarks and evaluation pipelines; and develop methods for multimodal and long-context handling. A key part of the role is transferring research into production, working closely with product and engineering teams to improve live systems, support model and prompt evaluation across the full lifecycle, and optimise latency, cost, and training data quality. Writing papers is welcome, but the primary goal is to ship research that improves real customer outcomes.
Master’s or PhD in Computer Science, AI, ML, Mathematics, Physics, or a related field
Hands-on experience with complex LLM/agentic systems and production-quality Python
Strong knowledge of Transformers, model training/inference, and prompt engineering
Ability to read, reproduce, and improve research papers
English business level or Japanese fluent
